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      Unveiling a novel transient druggable pocket in BACE-1 through molecular simulations: Conformational analysis and binding mode of multisite inhibitors

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          Abstract

          The critical role of BACE-1 in the formation of neurotoxic ß-amyloid peptides in the brain makes it an attractive target for an efficacious treatment of Alzheimer’s disease. However, the development of clinically useful BACE-1 inhibitors has proven to be extremely challenging. In this study we examine the binding mode of a novel potent inhibitor (compound 1, with IC 50 80 nM) designed by synergistic combination of two fragments—huprine and rhein—that individually are endowed with very low activity against BACE-1. Examination of crystal structures reveals no appropriate binding site large enough to accommodate 1. Therefore we have examined the conformational flexibility of BACE-1 through extended molecular dynamics simulations, paying attention to the highly flexible region shaped by loops 8–14, 154–169 and 307–318. The analysis of the protein dynamics, together with studies of pocket druggability, has allowed us to detect the transient formation of a secondary binding site, which contains Arg307 as a key residue for the interaction with small molecules, at the edge of the catalytic cleft. The formation of this druggable “floppy” pocket would enable the binding of multisite inhibitors targeting both catalytic and secondary sites. Molecular dynamics simulations of BACE-1 bound to huprine-rhein hybrid compounds support the feasibility of this hypothesis. The results provide a basis to explain the high inhibitory potency of the two enantiomeric forms of 1, together with the large dependence on the length of the oligomethylenic linker. Furthermore, the multisite hypothesis has allowed us to rationalize the inhibitory potency of a series of tacrine-chromene hybrid compounds, specifically regarding the apparent lack of sensitivity of the inhibition constant to the chemical modifications introduced in the chromene unit. Overall, these findings pave the way for the exploration of novel functionalities in the design of optimized BACE-1 multisite inhibitors.

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          PROPKA3: Consistent Treatment of Internal and Surface Residues in Empirical pKa Predictions.

          In this study, we have revised the rules and parameters for one of the most commonly used empirical pKa predictors, PROPKA, based on better physical description of the desolvation and dielectric response for the protein. We have introduced a new and consistent approach to interpolate the description between the previously distinct classifications into internal and surface residues, which otherwise is found to give rise to an erratic and discontinuous behavior. Since the goal of this study is to lay out the framework and validate the concept, it focuses on Asp and Glu residues where the protein pKa values and structures are assumed to be more reliable. The new and improved implementation is evaluated and discussed; it is found to agree better with experiment than the previous implementation (in parentheses): rmsd = 0.79 (0.91) for Asp and Glu, 0.75 (0.97) for Tyr, 0.65 (0.72) for Lys, and 1.00 (1.37) for His residues. The most significant advance, however, is in reducing the number of outliers and removing unreasonable sensitivity to small structural changes that arise from classifying residues as either internal or surface.
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            Translating cell biology into therapeutic advances in Alzheimer's disease.

            D. Selkoe (1999)
            Studies of the molecular basis of Alzheimer's disease exemplify the increasingly blurred distinction between basic and applied biomedical research. The four genes so far implicated in familial Alzheimer's disease have each been shown to elevate brain levels of the self-aggregating amyloid-beta protein, leading gradually to profound neuronal and glial alteration, synaptic loss and dementia. Progress in understanding this cascade has helped to identify specific therapeutic targets and provides a model for elucidating other neurodegenerative disorders.
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              rDock: A Fast, Versatile and Open Source Program for Docking Ligands to Proteins and Nucleic Acids

              Identification of chemical compounds with specific biological activities is an important step in both chemical biology and drug discovery. When the structure of the intended target is available, one approach is to use molecular docking programs to assess the chemical complementarity of small molecules with the target; such calculations provide a qualitative measure of affinity that can be used in virtual screening (VS) to rank order a list of compounds according to their potential to be active. rDock is a molecular docking program developed at Vernalis for high-throughput VS (HTVS) applications. Evolved from RiboDock, the program can be used against proteins and nucleic acids, is designed to be computationally very efficient and allows the user to incorporate additional constraints and information as a bias to guide docking. This article provides an overview of the program structure and features and compares rDock to two reference programs, AutoDock Vina (open source) and Schrödinger's Glide (commercial). In terms of computational speed for VS, rDock is faster than Vina and comparable to Glide. For binding mode prediction, rDock and Vina are superior to Glide. The VS performance of rDock is significantly better than Vina, but inferior to Glide for most systems unless pharmacophore constraints are used; in that case rDock and Glide are of equal performance. The program is released under the Lesser General Public License and is freely available for download, together with the manuals, example files and the complete test sets, at http://rdock.sourceforge.net/
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                15 May 2017
                2017
                : 12
                : 5
                : e0177683
                Affiliations
                [1 ]Laboratory of Pharmaceutical Chemistry, Faculty of Pharmacy and Food Sciences, and Institute of Biomedicine, University of Barcelona, Barcelona, Spain
                [2 ]Department of Nutrition, Food Science and Gastronomy, Faculty of Pharmacy and Food Sciences, and Institute of Biomedicine, Campus Torribera, University of Barcelona, Santa Coloma de Gramenet, Spain
                [3 ]School of Pharmacy and Centre for Biomolecular Sciences, University Park, Nottingham, United Kingdom
                Bioinformatics Institute, SINGAPORE
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: CAL FJL.

                • Formal analysis: ODP JJJ.

                • Funding acquisition: DMT CAL FJL.

                • Investigation: ODP JJJ.

                • Supervision: CAL FJL.

                • Visualization: ODP.

                • Writing – original draft: ODP DMT CAL FJL.

                [¤]

                Current address: EaStCHEM School of Chemistry, University of Edinburgh, Edinburgh, United Kingdom

                Author information
                http://orcid.org/0000-0003-1464-1397
                http://orcid.org/0000-0002-8140-8555
                http://orcid.org/0000-0002-8049-3567
                Article
                PONE-D-16-46314
                10.1371/journal.pone.0177683
                5432175
                28505196
                fb65072b-9414-4feb-a8f7-b4f0dc0e9d81
                © 2017 Di Pietro et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 23 November 2016
                : 1 May 2017
                Page count
                Figures: 9, Tables: 0, Pages: 22
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100003329, Ministerio de Economía y Competitividad;
                Award ID: SAF2014-57094-R
                Award Recipient : Javier Luque
                Funded by: funder-id http://dx.doi.org/10.13039/501100002809, Generalitat de Catalunya;
                Award ID: 2014SGR1189
                Award Recipient : Javier Luque
                Funded by: funder-id http://dx.doi.org/10.13039/501100002809, Generalitat de Catalunya;
                Award ID: 2014SGR52
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100003741, Institució Catalana de Recerca i Estudis Avançats;
                Award Recipient : Javier Luque
                Funded by: Archer High Performance Computing
                Award Recipient :
                Funded by: Consorci de Serveis Universitaris de Catalunya
                Award Recipient : Javier Luque
                This work was supported by the Ministerio de Economía y Competitividad (SAF2014-57094-R), Generalitat de Catalunya (GC; 2014SGR1189, 2014SGR52), and ICREA Academia (FJL). The Consorci de Serveis Universitaris de Catalunya (CSUC; FJL) is acknowledged for providing computational resources. This work used the ARCHER UK National Supercomputing Service ( http://www.archer.ac.uk), via the HECBioSim consortium (EPSRC Grant EP/L000253/1). A fellowship from GC to ODP is gratefully acknowledged. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
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                Physical Sciences
                Chemistry
                Computational Chemistry
                Molecular Dynamics
                Biology and Life Sciences
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                Enzymology
                Enzyme Structure
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                Biochemical Simulations
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                Principal Component Analysis
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